envelope(boot)
envelope()所属R语言包：boot
Confidence Envelopes for Curves
曲线信心信封
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function calculates overall and pointwise confidence envelopes for a curve based on bootstrap replicates of the curve evaluated at a number of fixed points.
此函数计算的基础上引导曲线整体和逐点信心信封重复在一个固定点的数量计算的曲线。
用法----------Usage----------
envelope(boot.out = NULL, mat = NULL, level = 0.95, index = 1:ncol(mat))
参数----------Arguments----------
参数：boot.out
An object of class "boot" for which boot.out$t contains the replicates of the curve at a number of fixed points.
一个类的对象"boot"boot.out$t包含在一个固定点的曲线复制。
参数：mat
A matrix of bootstrap replicates of the values of the curve at a number of fixed points. This is a required argument if boot.out is not supplied and is set to boot.out$t otherwise.
一个矩阵的引导复制曲线在一个固定点的数量值。 boot.out如果不提供的，并设置为boot.out$t否则，这是一个必需的参数。
参数：level
The confidence level of the envelopes required. The default is to find 95% confidence envelopes. It can be a scalar or a vector of length 2. If it is scalar then both the pointwise and the overall envelopes are found at that level. If is a vector then the first element gives the level for the pointwise envelope and the second gives the level for the overall envelope.
所需的信封的信心水平。默认的是95％的信心信封。它可以是一个标量或向量的长度为2。如果它是标量，那么这两个点态和整体的信封被发现在该级别。如果是一个向量，那么第一个元素给出了水平的逐点的信封和第二，给人的整体信封水平。
参数：index
The numbers of the columns of mat which contain the bootstrap replicates. This can be used to ensure that other statistics which may have been calculated in the bootstrap are not considered as values of the function. </table>
mat其中包含引导复制的列的数字。这可以用来确保不考虑作为函数值，它可能已被计算在引导其他统计。 </ TABLE>
Details
详情----------Details----------
The pointwise envelope is found by simply looking at the quantiles of the replicates at each point. The overall error for that envelope is then calculated using equation (4.17) of Davison and Hinkley (1997). A sequence of pointwise envelopes is then found until one of them has overall error approximately equal to the level required. If no such envelope can be found then the envelope returned will just contain the extreme values of each column of mat.
逐点信封，发现通过简单地在每个点重复位数。戴维森和欣克利（1997）利用方程（4.17），然后计算该信封的整体错误。逐点信封的序列，然后发现，直到其中一人有总体误差约等于所需的水平。然后可以发现，如果没有这样的信封，信封返回只包含每个mat列极端值。
值----------Value----------
A list with the following components :
以下组件列表：
参数：point
A matrix with two rows corresponding to the values of the upper and lower pointwise confidence envelope at the same points as the bootstrap replicates were calculated.
一个相应的上限和下限，在引导的相同点逐点信心信封的价值与两行的矩阵复制进行了计算。
参数：overall
A matrix similar to point but containing the envelope which controls the overall error.
A矩阵类似point但含有控制整体错误的信封。
参数：k.pt
The quantiles used for the pointwise envelope.
位数用于逐点信封。
参数：err.pt
A vector with two components, the first gives the pointwise error rate for the pointwise envelope, and the second the overall error rate for that envelope.
两部分组成的一个向量，使错误率的逐点逐点的信封，该信封的第二个整体的错误率。
参数：k.ov
The quantiles used for the overall envelope.
位数用于整体信封。
参数：err.ov
A vector with two components, the first gives the pointwise error rate for the overall envelope, and the second the overall error rate for that envelope.
两部分组成的向量，首先给出了逐点误差率，整体信封和第二，信封整体的错误率。
参数：err.nom
A vector of length 2 giving the nominal error rates for the pointwise and the overall envelopes. </table>
一个向量的长度为2点态和整体信封的名义错误率。 </ TABLE>
参考文献----------References----------
Bootstrap Methods and Their Application. Cambridge University Press.
参见----------See Also----------
boot, boot.ci
boot，boot.ci
举例----------Examples----------
# Testing whether the final series of measurements of the gravity data[测试测量重力数据是否最后的系列]
# may come from a normal distribution. This is done in Examples 4.7 [可能来自正态分布。这是在范例4.7]
# and 4.8 of Davison and Hinkley (1997).[戴维森和欣克利（1997）的4.8％。]
grav1 <- gravity$g[gravity$series == 8]
grav.z <- (grav1 - mean(grav1))/sqrt(var(grav1))
grav.gen <- function(dat, mle) rnorm(length(dat))
grav.qqboot <- boot(grav.z, sort, R = 999, sim = "parametric",
ran.gen = grav.gen)
grav.qq <- qqnorm(grav.z, plot.it = FALSE)
grav.qq <- lapply(grav.qq, sort)
plot(grav.qq, ylim = c(-3.5, 3.5), ylab = "Studentized Order Statistics",
xlab = "Normal Quantiles")
grav.env <- envelope(grav.qqboot, level = 0.9)
lines(grav.qq$x, grav.env$point[1, ], lty = 4)
lines(grav.qq$x, grav.env$point[2, ], lty = 4)
lines(grav.qq$x, grav.env$overall[1, ], lty = 1)
lines(grav.qq$x, grav.env$overall[2, ], lty = 1)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-2-16 17:42:44
